Dr Timothy Chisholm works in the Yusuf Hamied Department of Chemistry at the University of Cambridge and is the Henslow Fellow at St Edmund’s College, Cambridge. Tim also completed his PhD at the Department, in the Hunter Group, and before joining St Edmund’s, he was a member of Trinity College.
Tim research aims to develop diagnostic methods for neurodegenerative diseases, and for Parkinson’s disease in particular. Ten million people are estimated to have Parkinson’s disease worldwide, with one million new cases being diagnosed each year. However, diagnosing Parkinson’s can be very challenging. One in four patients are initially misdiagnosed, and this initial diagnosis can take months to years.
Parkinson’s and other neurodegenerative diseases are characterised by protein aggregates; clumps of misfolded protein that appear in the brain. Tim’s PhD research focused on finding new molecules that cling to these aggregates, and on developing a better understanding as to how these molecules interact with aggregates. As a Henslow Fellow Timothy is expanding on this work to study several different aspects of neurodegenerative diseases. The ultimate goal of this research is to develop a diagnostic test that can identify Parkinson’s disease both earlier and more accurately.
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The dynamics of infectious disease (ID) require fast accurate diagnosis for effective management and treatment. Without affordable, accessible diagnostics, syndromic or presumptive actions are often followed, where positive cases may go undetected in the community, or mistreated due to wrong diagnosis. In many low and middle income countries (LMICs), this undermines effective clinical decision-making and infectious disease containment.
Unsteady effects occur in many natural and technical flows, for example around flapping wings or during aircraft gust encounters. If the unsteadiness is large, the resulting forces can be quite considerable. However, the exact physical mechanisms underlying the generation of unsteady forces are complex and their accurate prediction remains challenging. One strategy is to identify the dominant effects and describe these with simple analytical models, first proposed a hundred years ago. When used successfully, this approach has the advantage that it also gives us a conceptual understanding of unsteady fluid mechanics.
In this lecture I will explain some of these ideas and demonstrate how they can still be useful today. As a practical example, I will show how the forces experienced in a wing-gust encounter can be predicted – and how the predictions can be used to mitigate the gust effects. The lecture will be illustrated with images and videos from simple, canonical, experiments.
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